I’m afraid they already had that exact idea when they named the startup “oklo”.

I think it’s not very difficult to construct a really shitty small reactor that is horrendously expensive per watt. Can probably be built in a year if you get rid of NRC and just half ass it completely.

I mean, Demon Core was a small reactor. You pretty much have to do a lot of work to ensure you won’t create a small reactor when a truckload of fresh fuel falls into a river.

What’s difficult is making a safe reactor that is actually making electricity at somewhat reasonable price per watt.

Nuclear already makes 9% of world’s electricity.

Shorting the market requires precise timing. Being early is just as bad as being wrong.

Exactly. It is not enough to know that a company stock will go down. It is necessary to know that it will never go higher than a certain point above the current value (not even momentarily) before it goes down. If you have a fuckload of other people’s money you can just keep double-or-nothing-ing it, that’s what banks were doing to gamestop, except that this can sometimes cause the stock to go even higher (a short squeeze), which would make you (who doesn’t actually have a fuckload of other people’s money) lose all of your money.

edit: also the other concerning possibility is that stock prices can go up simply due to the dollar going down.

The only thing that is allowed to tell good art from slop is the AI which needs to consume good art and not slop.

Its spelled “masterdebating”.

Hyping up AI is bad, so it’s alright to call someone a promptfondler for fondling prompt.

I mostly see “clanker” in reference to products of particularly asinine promptfondling: spambot “agents” that post and even respond to comments, LLM-based scam calls, call center replacement, etc.

These bots don’t derive their wrongness from the wrongness of promptfondling, these things are part of why promptfondling is wrong.

Doesn’t clanker come from some Star Wars thing where they use it like a racial slur against robots, who are basically sapient things with feelings within its fiction? Being based on “cracker” would be alright,

I assume the writers wanted to portray the robots as unfairly oppressed, while simultaneously not trivializing actual oppression of actual people (the way “wireback” would have, or I dunno “cogger” or something).

but the way I see it used is mostly white people LARPing a time and place when they could say the N-word with impunity.

Well yeah that would indeed be racist.

I’m seeing a lot of people basically going “I hate naggers, these naggers are ruining the neighborhood, go to the back of the bus nagger, let’s go lynch that nagger” and thinking that’s funny because haha it’s not the bad word technically.

That just seems like an instance of good ol anti person racism / people trying to offend other people while not particularly giving a shit about the bots one way or the other.

we should recognize the difference

The what now? You don’t think there’s a lot of homophobia that follows “castigating someone for what they do” format, or you think its a lot less bad according to some siskinded definition of what makes slurs bad that somehow manages to completely ignore anything that actually makes slurs bad?

I think that’s the difference between “promptfondler” and “clanker”. The latter is clearly inspired by bigoted slurs.

Such as… “cracker”? Given how the law protects but doesn’t bind AI, that seems oddly spot on.

Note also that genuine labor saving stuff like say the Unity engine with Unity asset store, did result in an absolute flood of shovelware on Steam back in the mid 2010s (although that probably had as much having to do with Steam FOMO-ing about the possibility of not letting the next Minecraft onto Steam).

As a thought experiment imagine an unreliable labor saving tool that speeds up half* of the work 20x, and slows down the other half 3x. You would end up 1.525 times slower.

The fraction of work (not by lines but by hours) that AI helps with is probably less than 50% , and the speed up is probably worse than 20x.

Slowdown could be due to some combination of

• Trying to do it with AI until you sink too much time into that and then doing it yourself (>2x slowdown here).
• Being slower at working with the code you didn’t write.
• It being much harder to debug code you didn’t write.
• Plagiarism being inferior to using open source libraries.

footnote: “half” as measured by the pre-tool hours.

And yet you are the one person here who is equating Mexicans and Black people with machines. People with disabilities, too, huh. Lemme guess next time we’re pointing and laughing at how some hyped-up “PhD level chatbot” can’t count the Es in dingleberry, you’ll be likening that to ableism.

When you’re attempting to humanize machines by likening the insults against machines to insults against people, this does more to dehumanize people than to humanize machines.

edit: Also I never seen and couldn’t find instances of “wireback” being used outside pro-bot sentiments and hand-wringing about how anti bot people are akhtually racist. Had you, or is it all second or third hand? It’s entirely possible that it is something botlickers (can I say that or is that not OK?) came up with.

edit: especially considering that these “anti-robot slurs” seem to originate in scifi stories where the robots are being oppressed, whereby the author is purposefully choosing that slur to undermine the position of anti robot characters in the story. It may well be that for the same reason that author has in choosing these slurs, they are rarely used (in the earnest).

To be honest, hand wringing over “clanker” being a slur and all that strikes me as increasingly equivalent to hand wringing over calling nazis nazis. The only thing that rubs me the wrong way is that I’d prefer the new so called slur to be “chatgpt”, genericized and negative connotated.

If you are in the US, we’ve had our health experts replaced with AI, see the “MAHA report”. We’re one moron AI-pilled president away from a less fun version of Skynet, whereby a chatbot talks the president into launching nukes and kills itself along with a few billion people.

Complaints about dehumanizing these things is even more meritless than a CEO complaining that someone is dehumanizing Exxon (which is at least made of people).

These things are extension of those in power, not some marginalized underdogs like cute robots in scifi. As an extension of corporations, it already got more rights than any human - imagine what would happen to a human participant in a criminal conspiracy to commit murder and contrast that with what happens when a chatbot talks someone into a crime.

I think this is spot on. I had that same thing happen at my former employer, which bought a lot of entirely pointless startups in 2010s instead of investing in core business equipment and processes.

Even to the extent that they are “prompting it wrong” it’s still on the AI companies for calling this shit “AI”. LLMs fundamentally do not even attempt to do cognitive work (the way a chess engine does by iterating over possible moves).

Also, LLM tools do not exist. All you can get is a sales demo for the company stock (the actual product being sold), built to impress how close to AGI the company is. You have to creatively misuse these things to get any value out of them.

The closest they get to tools is “AI coding”, but even then, these things plagiarize code you don’t even want plagiarized (because its MIT licensed and you’d rather keep up with upstream fixes).

The problem is that to start breaking encryption you need quantum computing with a bunch of qubits as originally defined and not “our lawyer signed off on the claim that we have 1000 qubits”.

Yeah, the glorious future where every half-as-good-as-expert developer is now only 25% as good as an expert (a level of performance also known as being “completely shit at it”), but he’s writing 10x the amount of unusable shitcode.

When they tested on bugs not in SWE-Bench, the success rate dropped to 57‑71% on random items, and 50‑68% on fresh issues created after the benchmark snapshot. I’m surprised they did that well.

After the benchmark snapshot. Could still be before LLM training data cut off, or available via RAG.

edit: For a fair test you have to use git issues that had not been resolved yet by a human.

This is how these fuckers talk, all of the time. Also see Sam Altman’s not-quite-denials of training on Scarlett Johansson’s voice: they just asserted that they had hired a voice actor, but didn’t deny training on actual Scarlett Johansson’s voice. edit: because anyone with half a brain knows that not only did they train on her actual voice, they probably gave it and their other pirated movie soundtracks massively higher weighting, just as they did for books and NYT articles.

Anyhow, I fully expect that by now they just use everything they can to cheat benchmarks, up to and including RAG from solutions past the training dataset cut off date. With two of the paper authors being from Microsoft itself, expect that their “fresh issues” are gamed too.

lmao: they have fixed this issue, it seems to always run python now. Got to love how they just put this shit in production as “stable” Gemini 2.5 pro with that idiotic multiplication thing that everyone knows about, and expect what? to Eliza Effect people into marrying Gemini 2.5 pro?

Thing is, it has tool integration. Half of the time it uses python to calculate it. If it uses a tool, that means it writes a string that isn’t shown to the user, which runs the tool, and tool results are appended to the stream.

What is curious is that instead of request for precision causing it to use the tool (or just any request to do math), and then presence of the tool tokens causing it to claim that a tool was used, the requests for precision cause it to claim that a tool was used, directly.

Also, all of it is highly unnatural texts, so it is either coming from fine tuning or from training data contamination.

Hmm, fair point, it could be training data contamination / model collapse.

It’s curious that it is a lot better at converting free form requests for accuracy, into assurances that it used a tool, than into actually using a tool.

And when it uses a tool, it has a bunch of fixed form tokens in the log. It’s a much more difficult language processing task to assure me that it used a tool conditionally on my free form, indirect implication that the result needs to be accurate, than to assure me it used a tool conditionally on actual tool use.

The human equivalent to this is “pathological lying”, not “bullshitting”. I think a good term for this is “lying sack of shit”, with the “sack of shit” specifying that “lying” makes no claim of any internal motivations or the like.

edit: also, testing it on 2.5 flash, it is quite curious: https://g.co/gemini/share/ea3f8b67370d . I did that sort of query several times and it follows the same pattern: it doesn’t use a calculator, it assures me the result is accurate, if asked again it uses a calculator, if asked if the numbers are equal it says they are not, if asked which one is correct it picks the last one and argues that the last one actually used a calculator. I hadn’t ever managed to get it to output a correct result and then follow up with an incorrect result.

edit: If i use the wording of “use an external calculator”, it gives a correct result, and then I can’t get it to produce an incorrect result to see if it just picks the last result as correct, or not.

I think this is lying without scare quotes, because it is a product of Google putting a lot more effort into trying to exploit Eliza effect to convince you that it is intelligent, than into actually making an useful tool. It, of course, doesn’t have any intent, but Google and its employees do.

Pretentious is a fine description of the writing style. Which actual humans fine tune.